Candida species are commensally microorganisms in healthy
individuals, but is also the most opportunistic fungal pathogen of
human. From benign skin-mucosal forms to invasive ones, Candida
infection, can compromise various organs systematic and cause
diseases in immunocompromised or critically ill patients. Hence the
accurate identification and characterization of the disease-causing
strains is crucial for diagnosis, clinical treatment and epidemiological
studies of candidacies. Molecular methods the identification and
characterization support gives in epidemiological research and in
development of novel antifungal with specific molecular targets,
especially in the case of resistant Candida species. This review
aims to describe the main methods used in the identification
and characterization the Candida species and discusses future
perspectives.

Keywords: Candidiasis; ITS; Genomes; Molecular typing

Introduction

Candida species commensally inhabit the human body. The
relationship between an autochthonous Candida species and
its human host can be affected by pathological, physiological,
mechanical and iatrogenic factors. In this sense, Candida species
can cause several types of infections with a wide spectrum of
clinical presentations, from superficial benign forms to invasive
ones that compromise several organs, leading to host death [1].
Candida species exhibit a large clinical relevance, therefore is
necessary to correctly identify and characterize the isolates at the
molecular level for understanding the spread of species and the
mechanisms of their resistance to antifungal agents [2].

The resistance of Candida species to antifungal agents
can often be attributed to a mutation gene or other alteration
(such as increased expression) of the drug target [3]. In this
sense, were developed several effective molecular methods
for the identification and characterization of Candida species.
These methods support gives in epidemiological research and
in development of novel antifungal with specific molecular
targets, especially in the case of resistant Candida species.
This review summarizes the insights the main methods used
in the identification and characterization the Candida species
and discusses future perspectives: omics technologies for
characterization of Candida species.

General features: Candida species

Candida species are taxonomically classified in the kingdom
Fungi, phylum Ascomycota, class Saccharomycetes, family
Saccharomycetaceae, and genus Candida. These yeasts are
unicellular microorganisms that are pleomorphic and ovoid
or spherical in shape with an incomplete sexual cycle. Candida
species commensally inhabit the human body and can be found in
the respiratory tract, gastrointestinal tract, vaginal mucosa, oral
cavity, and skin of healthy individuals [4]; they can also be isolated
from plants, water, soil, and other environments. Moreover, they
can degrade proteins and carbohydrates as a source of carbon
and nitrogen, which are essential for their development [5].

The relationship between an autochthonous Candida species
and its human host can be affected by pathological, physiological,
mechanical, and iatrogenic factors. In this sense, Candida species
can cause several types of infections with a wide spectrum of
clinical presentations, from superficial benign forms to invasive
ones that compromise several organs, leading to host death [1].

There are close to 200 different Candida species, five of which
Candida albicans, Candida tropicalis, Candida glabrata, Candida
krusei, and Candida parapsilosis [subdivided into C. parapsilosis,
Candida orthopsilosis, and Candida metapsilosis] (Figure 1) are
involved in more than 90% of invasive infections [6,7]. Other
emergent Candida species, such as Candida guilliermondii,
Candida dubliniensis, Candida lusitaniae, Candida kefyr, Candida
rugosa, Candida famata, Candida utilis, Candida lipolytica, Candida
norvegensis, and Candida inconspícua, also have clinical relevance,
and have been identified as causative agents of superficial and
systemic itches [7,8].

C. albicans is considered the most frequently isolated species
from patients with superficial and invasive infections of different

anatomical sites in case studies from around the world [9]. Its
main pathogenic mechanisms and virulence factors appear to be
its ability to adhere to different mucous membranes and epithelia,
its ability to produce filamentous structures that assist in tissue
invasion, and its production of enzymes such as proteinases and
phospholipases. Such species are naturally sensitive to antifungal
agents when used systemically, but cases of acquired resistance
to azolics, in particular to fluconazole, have been described in
patients that receive long-term antifungal therapy [10].

In Latin American countries, especially Brazil, C. tropicalis is
detected in 20-24% of blood-borne infections [10,11], mainly in
elderly patients and those with conditions such as neutropenia
and Diabetes mellitus [12]. Clinical isolates of this species are
typically sensitive to amphotericin B and triazoles [13]; however,
cases of resistance to these drugs, especially to fluconazole, have
been recently reported and described [14].

The species C. glabrata and, C. krusei also have pathogenic
potential [10,11]. C. glabrata ranks second among isolates from
blood-borne infections in the United States. This species has
also experienced an increase in the percentage of fluconazoleresistant
isolates as well the incidence of isolates with reduced
sensitivity to amphotericin B and cross-resistance to other
drugs from the azole class [10]. C. krusei has been shown to
be an occasional hospital pathogen, particularly in patients
with hematological malignancies and/or that undergoing
bone marrow transplantation. C. krusei is naturally resistant to
fluconazole [15].

C. parapsilosis has been isolated from health professional
studies and parenteral nutrition solutions [16]. This yeast has
been recognized as a major cause of candidemia related to
infections that begin from the skin [17]. In general, clinical isolates
of this species are sensitive to most antifungal agents, especially
amphotericin B and azoles. However, in clinical studies, isolates
with reduced sensitivity to fluconazole have been reported [18].
Together, Candida species exhibit a large clinical relevance due
to their incidence of colonization and infection of the human
body. It is therefore necessary to correctly identify and diagnose
the yeast species responsible for an infection and subsequently
prescribe the proper antifungal agent for treatment.

Phenotypic methods used in the identification and
characterization of Candida species are based on analysis of
morphological and biochemical profile of these organisms.
The most widely used phenotypic methods for identification
and characterization the Candida species are observation of
microscopic structures, evaluation tests of enzyme activity and
assimilative capacity and substrate fermentation [19].

Several commercial products and systems have been
developed the aim of solve some difficulties experienced by the
clinical microbiology laboratories in the diagnosis of infections
caused by Candida species [20], for example Agar containing
chromo gens, kits and panels semi or full automated to the
presumed or definitive identification of the most prevalent species
[21,22]. The use of only phenotypic testing is not highly effective
for identification of Candida species because some species
has few morphological and biochemical variations, therefore
phenotypic and molecular methods can be used in together to
increase reliability in the identification of these species.

Identification and Molecular Characterization

In recent decades, molecular biological techniques have been
used to better understand the pathogenicity of Candida species
and to expand the search for new molecular drug targets. Candida
species are diploid, heterozygous, and contain a plastid genome,
features which recent genomic approaches have been able to
better characterize. In 1996, the Candida Genome Sequencing
Project was initiated with a goal of sequencing the genome of
C. albicans SC5314 [23,24]. This goal necessitated the use of
bioinformatics tools that were able to predict and annotate genes
in the sequence. The result was the description of 6,354 genes,
although the DNA sequences of some specific chromosomes had
still not been determined.

Comparison of the C. albicans genome with the genomes of
other fungal species allowed for the identification of several
specific genes that could be potential targets for antifungal
therapies. It was observed that compared with other fungi, the
coding sequence of the C. albicans genome was rich in short
tandem repeats (STRs). It was also possible to identify and
conduct detailed analyses of multi genic families found in C.
albicans, many of which were related to its pathogenicity [23].

In 2007, Van Het Hoog, et al. [25] provided the complete
sequence of the C. albicans SC5314 genome (15.845 Mb organized
into 8 chromosomes). In addition to its utility for genetic
mapping, it provided updates for certain genome characteristics,
including the discovery of an additional transcription factor gene
family, information concerning the chromosomal locations of
gene families, and a review of the open reading frame (ORF) list
previously annotated by Braun, et al. [23].

The genomes of the species sequenced by Butler, et al. [26]
ranged in both size (between 10.6 to 15.5 Mb) and composition
of protein-coding genes (5,733–6,318 genes) across the
different species. The authors also identified 64 gene families
that appeared to be related to Candida pathogenicity. Six of
these families had been previously shown to be associated with
pathogenicity, including the ERG3 gene, which is involved in
the ergosterol biosynthesis pathway. The dissemination of C.
albicans and Non-albicans Candida (NAC) genomes in the public
domain accelerated research on the biological and molecular
mechanisms associated with the pathogenicity of these species.

Due to the fact that some species of Candida present few
easily identifiable morphological and biochemical variations,
molecular biological techniques have been used to overcome
the limitations of phenotypic identification methods. Fungal
molecular systematic is based primarily on the analysis of
mitochondrial genes (mtDNA) and ribosomal DNA (rDNA) [28].

The mitochondrial cytochrome C oxidase subunit 1 (COI)
was proposed for molecular identification at the species level
[29]. This gene was adopted by the Consortium for the Barcode
of Life for the classification of all organismal groups, including
fungi [30]. COI works reasonably well as a barcode in some
fungi genera, such as Penicillium [31]; however, results in other
groups that have been experimentally examined are inconsistent,
limiting this gene’s use [32].

Ribosomal genes are conserved among all known organisms.
As a consequence, this gene allows for the joint reconstruction of
both prokaryotic and eukaryotic phylogenies. On the other hand,
the nucleotide substitution rate is low in the 18S rRNA gene [33],
often preventing discrimination between closely related species.
Thus, species that exhibit differences at the ribosomal gene level
have likely already been diverging for at least a few million years.

For discrimination of closely related filamentous fungal
species and yeasts, the Internal Transcribed Spacer regions (ITS
1 and ITS 2), located between the 18S, 5.8S, and 28S rRNA genes,
and the D1/D2 region, located in the larger rDNA subunit, have
shown to be successful in species-level identification (Figure 2).
In both ITS1 and ITS2, there are 100-200 tandem repeats, which
contain both highly conserved domains and variable domains,
respectively [34]. These regions have been adopted for use in
bar-coding for most fungi genera and are considered standard
markers by the Consortium for the Barcode of Life [35].

Kurztzman, et al. [36] described the presence of extensive
genetic differentiation in the D1/D2 region, allowing for the
differentiation of ascomycetes. Since then, this region, together

with the ITS regions, have been widely used for both identification
and establishment of evolutionary relationships (phylogenies)
of several fungi species, including Candida species. Phylogenies
inferred from molecular data have been used to clarify the main
evolutionary divisions between taxa, as well as helping in the
identification process of higher taxonomic groups, including the
Fungi kingdom [28].

Evolutionary histories as elucidated by phylogenetic
analysis are normally illustrated as branching, treelike diagrams
that represent estimates of inherited relationships between
molecules (phylogenetic tree), organisms, or both [37]. There
are three classes of phylogenetic methods: distance-based,
character-based, and Bayesian inference-based. In models that
use distances for phylogenetic reconstruction, two steps are
necessary: distance calculation and construction of the topology.

For distance-based calculation, calculated matrices are used
for pair wise comparisons between the aligned sequences based
on a replacement model, i.e., an evolutionary model of these
sequences. Among the most widely used models for phylogenetic
analysis in Candida are the P Distance, Juckes-Cantor, Kimura
2-parameter, Tajima and Nei, Tamura 3-Parameter, Tamura
and Nei, Gamma-Poisson, and PAM Distance models. The most
common algorithms used to order the calculated distances
between the macromolecular sequences contained in the matrix
into a topology are UPGMA (Unweighted Pair Group Method with
Arithmetic Mean), Neighbor-Joining, and Minimum Evolution
[38].

The character-based models are directly inspired by the
cladistics methods of Maximum Parsimony and Maximum
Likelihood [39]. For models based on Bayesian inference, the
parameters are considered random variables in which the
uncertainty about values is measured by the distribution of
posterior probabilities [40].

Many techniques are used for molecular characterization
of Candida species, such as Restriction Fragment Length
Polymorphism (RFLP) [41], DNA fingerprinting [42],
electrophoretic karyotyping [43], Random Amplified Polymorphic
DNA (RAPD) [44], Multilocus Enzyme Electrophoresis (MLEE)
[45], and sequencing of microsatellites [46]. However, in order to
estimate genetic distances and infer phylogenetic relationships
between species that can be easily evaluated in terms of
probability models, the most suitable techniques involve gene
sequencing and produce topologies built from nucleotide or
amino acid sequences.

One of the techniques used for molecular characterization are
the microarrays. Microarray-based systems offer an attractive
outlook for the of strain typing. They can offer high level of
specificity, sensitivity and through put capacity. For typing
molecular, microarrays can be used to identification and get the
different sequence variants of specific genes or regions and ITSs,
in particular. Ongoing sequencing projects in pathogenic yeasts
also enable quite straightforward designing of whole-genome
DNA microarrays [47].

Multilocus Sequence Typing (MLST), a sequencing-based
method, was initially developed for both clone identification and
bacterial pathogen typing [48]. This method analyzes nucleotide
polymorphisms in essential genes fragments, the “housekeeping
genes,” and can produce sequences of up to 500 bp [48-50],
generating a molecular characterization with high discriminatory
power and reproducibility.

The MLST technique has been used previously for several
Candida species, among them, C. albicans [49,51]. Based on
collaborative work, a set of seven essential C. albicans genes
were proposed for the analysis [52]. This set includes AAT1a,
ACC1, ADP1, SYA1, VPS13, ZWF1b, and MPIB, which has since
been renamed PMI1 [53]. MLST proved to be a useful method for
epidemiological differentiation of clinical isolates of C. albicans
[49,51].

Tavanti, et al. [54] found MLST on a panel of 416 isolates
of C. albicans from different sources recognized a population
structure comprising four major clades and eight minor clades.
Odds, et al. [55] evaluated larger panel of C. albicans isolates
(1391) for MLST analysis, the number of clades recognized
increased to clades 17. ABC types (based on the presence or
absence of an intron in rDNA) and geographical origins showed
statistically significant variations among clades, but anatomical
source and antifungal-susceptibility data were not significantly
associated. Computational haplotype analysis of the gene
fragments sequenced for MLST showed a high frequency of
recombination events, which suggests that C. albicans isolates
had mixed evolutionary histories resembling those of a sexually
reproducing species [55]. Also mitochondrial genes have been
demonstrated by Wang, et al. [56], to be promising targets for
genotyping and population genetics of C. albicans.

Ge, et al. [57] evaluated C. albicans isolates from the vagina
and oral cavity of Chinese candidose vulvovaginal patients and
asymptomatic carriers. The genotypes of these strains were
identified. Antifungal susceptibility testing revealed that the two
dominant genotypes, CAI 30–45 and CAI 32–46 associated with
vulvovaginitis showed significantly different azole-susceptibility.
Different mutation patterns in the azole target gene ERG11
were correspondingly observed among C. albicans isolates
representing different genotypes and sources. Isolates with
the same or similar CAI genotypes usually possessed identical
or phylogenetically closely related ERG11 sequences. Loss of
heterozygosity in ERG11 was observed in all the CAI 32–46
isolates but not in the CAI 30–45 isolates and most of the oral
isolates sequenced. Compared with the ERG11 sequence of strain
SC5314, two homozygous nonsynonymous substitutions, leading
to two amino-acid changes (A114S and Y257H) in the Erg11p
were found in CAI 32–46 isolates. The association between
azole-susceptibility and C. albicans genotype may be of potential
therapeutic important.

Dodgson, et al. [58] developed MLST for C. glabrata through
amplification and sequencing of fragments from the coding
regions of six genes (FKS, LEU2, NMT1, TRP1, UGP1, and URA3).
An MLST analysis of 230 C. glabrata isolates from five populations
that differed both geographically and temporally confirmed that
using the six loci, it was possible to assess genetic diversity and
differentiation among isolates of this species [59].

Tavanti, et al. [60] described a high degree of reproducibility
and discriminatory power above 99% when using MLST to
differentiate between isolates of C. tropicalis through sequencing
of polymorphic fragments of six genes (MDR1, ICL1, SAPT2, SAPT4,
XYR1, and ZWF1a). The method could differentiate between 87 of
the 106 DST isolates tested. Jacobsen, et al. [61] later conducted
a MLST study of the C. tropicalis molecular phylogeny with 242
isolates; the haplotype analysis revealed several recombination
events.
While conducting a molecular characterization study of 61
isolates of C. tropicalis, Magri, et al. [62] found that only 3 isolates
were resistant to fluconazole, but it was not possible to correlate
the Diploid Sequence Types (DSTs) with resistance. These same
authors reported that MLST is an important tool for the study
of genetic diversity, particularly with regard to polymorphisms.
Although many molecular studies have been conducted to
analyze the different Candida species, more research is needed
to investigate the genetic and phylogenetic diversities of Candida
species and their relation to epidemiology. The development of
next-generation sequencing (NGS) over recent years has allowed
a technological breakthrough in the molecular characterization
of Candida species. This technology allows accurate and thorough
genotyping of genes involved in antifungal resistance in strains
clinical. Garnoud, et al. [63] used NGS to investigate echinocandin
and azole resistance in clinical Candida isolates. Six genes
involved in antifungal resistance (ERG3, ERG11, TAC1, CgPDR1,
FKS1 and FKS2) were analyzed in 40 Candida isolates (18
C.albicans, 15 C.glabrata and 7 C.parapsilosis).
A total of 391 SNPs
were detected, among which 6 coding SNPs were reported for the
first time. Novel genetic alterations were detected in both azole
and echinocandin resistance genes. A C. glabrata strain, which
was resistant to echinocandins but highly susceptible to azoles,
harboured an FKS2 S663P mutation plus a novel presumed lossof-
function CgPDR1 mutation. Another C. glabrata isolate, carried
a new FKS2 S663A mutation and a new putative gain-of-function
CgPDR1 mutation (T370I). This study shows that NGS can be
used for extensive assessment of genetic mutations involved in
antifungal resistance.

Genome sequencing of Candida species provides the
opportunity to elucidate some of the mechanisms involved in
intrinsic or acquired resistance by yeasts of the Candida genus.
The omics technologies (genome, transcriptome, proteome,
metaboiome, microbiome and mycobiome) will become very
valuable for detecting mechanisms of resistance in clinical
strains subjected to multidrug pressure. The high-throughput
sequencing methods still has little practicability and feasibility
in daily clinical practice and thus still remains challenging, but
as future perspectives, current rapid progression of automation
of these technologies makes their upcoming routine application
likely.

Acknowledgements

This review did part of project supported by a grant from
the Foundation to Support the Development of Education,
Science and Technology of Mato Grosso do Sul ( FUNDECT ) and
the Higher Education Personnel Improvement Coordination
(CAPES), Mato Grosso do Sul, Brazil.